urdu-sentiment-model

🧠 Urdu Sentiment Analysis Model

This model performs sentiment analysis on Urdu text using a fine‑tuned XLM-RoBERTa transformer model.

It classifies input text into:

✅ Positive
❌ Negative
⚖️ Neutral

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📊 Model Details

• Architecture: XLM-RoBERTa
• Framework: PyTorch
• Task: Text Classification (Sentiment Analysis)
• Language: Urdu

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🚀 Usage Example

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

model_name = "abd12-tahir/urdu-sentiment-model"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)

text = "میں آج بہت خوش ہوں"

inputs = tokenizer(text, return_tensors="pt")

outputs = model(**inputs)

pred = torch.argmax(outputs.logits, dim=1)

print(pred)